Visible Light Communicationbased Vehicletovehicle Tracking Using Cmos Camera

• doi: 10.1109/ACCESS.2018.2890435
• title: Visible Light Communication-Based Vehicle-to-Vehicle Tracking Using CMOS Camera
• publisher: IEEE
• isbn:
• issn: 2169-3536
• rank: 3969
• access_type: OPEN_ACCESS
• content_type: Journals
• abstract: This paper presents a visible light-communication-based vehicle-to-vehicle tracking system using a new positioning algorithm and modified version of the Kalman filter. In this system, LED head and tail lamps on the vehicles are used to transmit the positioning signals to other vehicles. Two CMOS dashboard cameras on each vehicle are used to receive these signals. From the geometric relationship between two cameras and the images of LEDs captured by these two cameras, the instantaneous position of the target vehicle can be determined, given that at least one LED of the target vehicle is in the view frame of the two cameras. The discrete positioning result always contains unavoidable errors, which consist of systematic errors caused by the CMOS rolling shutter artifact and the weak spatial separability of the sensor, and other random errors. The contribution of this paper is twofold. First, a new positioning algorithm with two compensation mechanisms is proposed to eliminate systematic errors. Second, a modified Kalman filter is proposed to filter out random errors to achieve a smooth and accurate tracking result for the vehicle position. The performance of the system is verified through simulations.
• article_number: 8598724
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8598724
• html_url: https://ieeexplore.ieee.org/document/8598724/
• abstract_url: https://ieeexplore.ieee.org/document/8598724/
• publication_title: IEEE Access
• conference_location:
• conference_dates:
• publication_number: 6287639
• is_number: 8600701
• publication_year: 2019
• publication_date: 2019
• start_page: 7218
• end_page: 7227
• citing_paper_count: 19
• citing_patent_count: 0
• download_count: 2102
• insert_date: 20190101
• index_terms:
  • ieee_terms:
    • Cameras
    • Kalman filters
    • Image sensors
    • Light emitting diodes
    • Systematics
    • Target tracking
    • Vehicular ad hoc networks
  • author_terms:
    • Visible light communication
    • vehicle
    • tracking
    • camera
    • Kalman filter
  • dynamic_index_terms:
    • System Performance
    • Systematic Errors
    • Random Error
    • Tracking System
    • Tracking Devices
    • Kalman Filter
    • Spatial Separation
    • Head And Tail
    • Coin Flip
    • Coin Toss
    • Geometric Relationship
    • Vehicle Position
    • Vehicle Location
    • Tracking Results
    • Target Vehicle
    • Discrete Positions
    • Rolling Shutter
    • Weak Separation
    • Least Squares Regression
    • Linear Least Squares
    • Positioning System
    • Statistical Information
    • Position Error
    • Image Sensor
    • Camera Sensor
    • Types Of Sensors
    • Visible Light Communication
    • Intelligent Transportation Systems
    • Pinhole Camera Model
    • Pinhole Projection
    • True Distance
    • Linear Least Squares Method
    • Linear Least-squares Method
    • Sources Of Systematic Error
    • Optimal Estimation
    • Optimal Approximation
    • Vehicle State
    • Vehicle Conditions
    • Image Coordinates
    • Error Component
• authors:
  • Author Name: Trong-Hop Do
    Affiliation: School of Electronic Engineering, Soongsil University, Seoul, South Korea
    Author URL: https://ieeexplore.ieee.org/author/38468172800
    ID: 38468172800
    Order: 1
    Author Affiliations:
    • School of Electronic Engineering, Soongsil University, Seoul, South Korea
  • Author Name: Myungsik Yoo
    Affiliation: School of Electronic Engineering, Soongsil University, Seoul, South Korea
    Author URL: https://ieeexplore.ieee.org/author/37299835700
    ID: 37299835700
    Order: 2
    Author Affiliations:
    • School of Electronic Engineering, Soongsil University, Seoul, South Korea

Image Sensor

• sensor_type: CMOS
• resolution: Not specified in the paper.
• dynamic_range: Not specified in the paper.
• pixel_size: Not specified in the paper.
• dark_current: Not specified in the paper.

Optical Data

• focal_length: Not specified in the paper.
• aperture: Not specified in the paper.
• field_of_view: Not specified in the paper.
• distortion: Not specified in the paper.

Performance Metrics

• frame_rate: Not specified in the paper.
• signal_to_noise_ratio: Not specified in the paper.
• sensitivity: Not specified in the paper.
• shutter_speed: Not specified in the paper.
• power_consumption: Not specified in the paper.
• noise: Not specified in the paper.

Applications & Benefits

• cell_imaging: Used in various applications, although specifics are not detailed in the paper.
• benefits: CMOS image sensors enable digital imaging in smartphones, medical devices, and automotive systems.

Supporting Organizations

• supported_by: Information not available in this document.

Manuscript Details

• publication_date: 2019

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

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